|
|
Sentiment analysis of social networks
Zaplatílek, Jan ; Jelínek, Ivan (advisor) ; Bruckner, Tomáš (referee)
This thesis concerns about sentiment analysis. In more detail sentiment analysis of social networks. Main goal of sentiment analysis is determine if tested document expresses any sentiment and, if so, whether is positive or negative. Main reason for sentiment analysis on social networks is detecting sentiment and feels about some company or brand. This activity is called brand monitoring. Information acquired from brand monitoring can be used for improving marketing or communication with customers. This thesis deals with sentiment analysis of post from public Facebook profiles of several Czech banks and telecommunication operators. Goal of this thesis is create model which has precision of determine sentiment of Facebook posts at least 80%. Method for achieving this goal is experiment. First part of this thesis describes sentiment analysis theory, definition of sentiment analysis, its problems, methods, reasons for use and use cases of sentiment analysis. Second part gives background research of often used methods and data sources for sentiment analysis in foreign research. Finally third part of this theses describes experiment, its preparation and results. Main benefit of this theses is creating model which can be later use in real word.
|
|
|
Options of automated categorization of contracts
Bereš, Miroslav ; Jelínek, Ivan (advisor) ; Oškera, Radek (referee)
My bachelor thesis is focused on automatic categorization. The main goal is to examine actual approaches in automatic categorization, propose methodology for an experiment and perform the experiment. The experiment is done in order to measure success rate of automatic categorization with use of machine learning. It is performed on contracts obtained from public administration's web pages. The bachelor is divided into two parts, theoretical part and the experiment. First one focuses on analyzing theory which explains the subject matter, there are also described current approaches in automatic categorization. Second part describes methodology proposal of the experiment and performing of the experiment. During the process of the experiment, there are created models that are applied on control group. The experiment's outputs are categorized documents. These documents are used to monitor the success rate of automatic categorization. In order to measure the success rate, there is software called Apache OpenNLP used in this experiment. The theoretical part and proposal of the methodology are written based on studying foreign professional literature, mostly obtained from electronic and information sources.
|
|
|
Design of a system for recommending job opportunities
Paulavets, Anastasiya ; Mittner, Jan (advisor) ; Buchalcevová, Alena (referee)
This thesis deals with recommender systems in the field of e-recruitment. The main objective is to design a job recommender system for career portal UNIjobs.cz. First, the theoretical background of recommender systems is provided. In the following part, specific properties of job recommender systems are discussed, as well as existing approaches to recommendation in the e-recruitment environment. The last part of the thesis is dedicated to designing a recommender system for career portal UNIjobs.cz. The output of that part is the main contribution of the thesis.
|
|
|
Převod vybraných algoritmů data-mining z jazyka Java do binární (.exe) formy
Šrom, Jakub
There are many successful systems for data-mining (eg. WEKA, RapidMiner, etc.), which currently hold many algorithms implemented in Java, which allows their use under different operating systems. The disadvantage of the interpreted source code is a slowdown in the calculation and limited memory usage. The thesis is focused on the transfer of several selected implementations of algorithms in Java binaries (.exe) through the conversion of source code in C ++ under MS Windows 7 64-bit. The aim is to speed up calculations and improve management of memory usage. Binary form must give identical results as the original form. In addition to the actual transfer, the thesis also includes comparing time and memory requirements of the original (using the Java Runtime Environment, JRE) interpreted implementation in Java (JRE 64-bit) and x64 resulting binary forms, for selected test data.
|
|
| |
|
| |
|
|
Extracting Structured Data from Czech Web Using Extraction Ontologies
Pouzar, Aleš ; Svátek, Vojtěch (advisor) ; Labský, Martin (referee)
The presented thesis deals with the task of automatic information extraction from HTML documents for two selected domains. Laptop offers are extracted from e-shops and free-published job offerings are extracted from company sites. The extraction process outputs structured data of high granularity grouped into data records, in which corresponding semantic label is assigned to each data item. The task was performed using the extraction system Ex, which combines two approaches: manually written rules and supervised machine learning algorithms. Due to the expert knowledge in the form of extraction rules the lack of training data could be overcome. The rules are independent of the specific formatting structure so that one extraction model could be used for heterogeneous set of documents. The achieved success of the extraction process in the case of laptop offers showed that extraction ontology describing one or a few product types could be combined with wrapper induction methods to automatically extract all product type offers on a web scale with minimum human effort.
|
|
|
Extrakce informací z webových stránek pomoci extrakčních ontologií
Labský, Martin ; Berka, Petr (advisor) ; Strossa, Petr (referee) ; Vojtáš, Peter (referee) ; Snášel, Václav (referee)
Automatic information extraction (IE) from various types of text became very popular during the last decade. Owing to information overload, there are many practical applications that can utilize semantically labelled data extracted from textual sources like the Internet, emails, intranet documents and even conventional sources like newspaper and magazines. Applications of IE exist in many areas of computer science: information retrieval systems, question answering or website quality assessment. This work focuses on developing IE methods and tools that are particularly suited to extraction from semi-structured documents such as web pages and to situations where available training data is limited. The main contribution of this thesis is the proposed approach of extended extraction ontologies. It attempts to combine extraction evidence from three distinct sources: (1) manually specified extraction knowledge, (2) existing training data and (3) formatting regularities that are often present in online documents. The underlying hypothesis is that using extraction evidence of all three types by the extraction algorithm can help improve its extraction accuracy and robustness. The motivation for this work has been the lack of described methods and tools that would exploit these extraction evidence types at the same time. This thesis first describes a statistically trained approach to IE based on Hidden Markov Models which integrates with a picture classification algorithm in order to extract product offers from the Internet, including textual items as well as images. This approach is evaluated using a bicycle sale domain. Several methods of image classification using various feature sets are described and evaluated as well. These trained approaches are then integrated in the proposed novel approach of extended extraction ontologies, which builds on top of the work of Embley [21] by exploiting manual, trained and formatting types of extraction evidence at the same time. The intended benefit of using extraction ontologies is a quick development of a functional IE prototype, its smooth transition to deployed IE application and the possibility to leverage the use of each of the three extraction evidence types. Also, since extraction ontologies are typically developed by adapting suitable domain ontologies and the ontology remains in center of the extraction process, the work related to the conversion of extracted results back to a domain ontology or schema is minimized. The described approach is evaluated using several distinct real-world datasets.
|
|
|
Split Softening as a Problem of Machine Learning
Dvořák, Jakub
Softening splits in decision trees has ability to grow up quality of a classifier. This article concerns with some aspects of an optimization task to find such softening that reaches the best classification on training data. Experiments show, that improvement occurs on test data as well.
|
|
|
Modern Methods for Exchange Rete Prediction
Buryan, Petr ; Taušer, Josef (advisor)
Tato práce se snaží nabídnout odpověď na otázku, zda má smysl při rozhodování o budoucím pohybu měnových kurzů brát ohled na výsledky vystupující z modelů získaných analýzou měnových kurzů a relevantních časových řad provedeného pomocí metod strojového učení. Účelem této práce je tak prozkoumat možnosti analýzy kurzů (ve formě časových řad) s důrazem na použití nových metod spočívajících svým těžištěm v oblasti umělé inteligence a strojového učení (neuronové sítě, algoritmus GMDH sítí).
|
guest ::
